Some things to consider when opting for graph databases in engineering applications. Graph databases have moved from a topic of academic study into the mainstream of information technology in the last ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

One technology experiencing a kind of renaissance is the graph database, which has existed for years but is finding new relevance in current cybersecurity contexts. (NicoElNino/Getty Images) Spurred ...

Master Data Management is a practice adopted when a company really gets serious about making use of its data. Based on recent trends and some emerging analyst research, it seems that when companies ...

It's often easier to understand the use cases for graph databases than understanding how graph databases work. For instance, asking the question of who the most powerful thought leaders across ...

Graph databases are gaining attention as enterprises work on their next-generation artificial intelligence (AI) applications. While still a bit of an outlier, graph-oriented databases continue to find ...

This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big Data Analytics. What is a graph database? Graph databases organize facts into connected bundles, ...

Mirror mirror on the wall, who’s the Graphest database of them all? It depends. RDF is a graph data model that has been around since 1997. It’s a W3C standard, and it’s used to power schema.org and ...

Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...

The main objective of NoSQL databases is improved efficiency. It is somewhat achieved with the use of new technologies and thinking outside the box. An example of the new technologies applied could be ...